Method of Determining Parking Area Layout

ABSTRACT

Disclosed herein are methods of determining a layout for a parking area. In an aspect, a method includes determining environmental information about a surrounding environment of a vehicle moving in a parking area from sensing data provided by a sensing system of the vehicle; extracting parameters associated with parking slots identified from the environmental information; determining layout models for the parking area based at least on the extracted parameters, each layout model including an underlaying parking slot template; assigning to each of the determined layout models a confidence score; and selecting the layout model of the parking area having the highest confidence score as a current layout model used to determine the layout, the selected layout model is updated over time based on the confidence scores assigned to the layout models generated from sensing data collected while the vehicle is moving.

INCORPORATION BY REFERENCE

This application claims priority to United Kingdom Patent ApplicationNumber GB2205719.4, filed Apr. 19, 2022, the disclosure of which isincorporated by reference in its entirety.

BACKGROUND

In the automotive field, parking systems have been developed to controlthe vehicle in executing parking maneuvers in an automated manner orpartially automated manner. The parking systems rely on multiplesensors, e.g. vision sensors, Lidar sensors, radar sensors, GlobalNavigation Satellite System (GNSS), and a perception stack to collectinformation about a surrounding environment of the vehicle, and detect afree or unoccupied parking slot, also termed as parking space. Once afree parking slot has been detected and confirmed, the parking systemstarts planning a parking maneuver and then controls at least partiallythe vehicle to execute the planned parking maneuver.

Before planning the parking maneuver, the parking system accumulatesevidences of occupancy from the perception stack, post process theevidences of occupancy to detect gaps between occupied spaces andclassify detected gaps as parking slots. After detection of a parkingslot, the slot occupancy status is tracked and, if the slot isunoccupied, a path is planned to perform the parking maneuver to parkthe vehicle in the unoccupied parking slot.

The existing parking systems are effective in controlling the vehicle toperform automated or partially automated parking maneuvers. However,they have a high latency. The algorithms implemented for planning theparking maneuver have to wait for a confirmation that a detected gap isunoccupied and can fit the vehicle, which can generally be performedonly after passing it by. As a result, the overall execution time for aparking maneuver controlled by the parking system is significantlyincreased.

The present disclosure allows to improve the situation. In particular,there is a need for facilitating maneuvers for a vehicle in a parkingarea.

SUMMARY

The present disclosure concerns a computer-implemented method ofdetermining a layout for a parking area, comprising the following steps:determining environmental information about a surrounding environment ofa vehicle from sensing data provided by a sensing system of saidvehicle, while the vehicle is moving in the parking area; determining alayout for the parking area by performing the steps of: extracting oneor more parameters associated with parking slots identified from theenvironmental information; determining one or more layout models for theparking area based at least on the extracted one or more parameters,each layout model comprising an underlaying parking slot template;assigning to each of the determined layout models a confidence score,indicating how the respective underlaying parking slot template matchesthe one or more parameters associated with the parking slots identifiedfrom the environmental information; and selecting the layout model ofthe parking area having the highest confidence score as a current layoutmodel used to determine the parking area layout; wherein, the selectedlayout model is updated over time based on the confidence scoresassigned to the layout models generated from sensing data collectedwhile the vehicle is moving.

The determined parking area layout can be used to control one or morefunctions of the vehicle. For example, the determined parking arealayout can be used by a path planning module of the vehicle, to betterplan a trajectory within the parking area for the vehicle. The vehiclecan be controlled to move along the planned trajectory in an automatedor at least partially automated manner. This allows faster, smoother andmore secure maneuvers of the vehicle in the parking area.

Advantageously, the determined parking area layout is used to control adriving trajectory of the vehicle and/or an Advanced Driver AssistanceSystems (ADAS) control function.

For example, the method may also include a step of controlling thevehicle to move along a driving trajectory planned using the determinedparking area layout, in an automated or partially automated manner.

In an embodiment, the method may further include a step of assigning anoccupancy status score to each of a plurality of parking slot elementsof the layout of the parking area, indicating a probability of occupancyof said parking slot, and updating the occupancy status scores based onthe environmental information.

In an embodiment, a score indicating an unoccupied status may beassigned by default to each of the parking slot elements of the layoutof the parking area, unless the environmental information provides anoccupancy indication for said parking slot element.

Advantageously, the method may further include a step of identifying anunoccupied parking slot based on the occupancy status score assigned toeach of the plurality of parking slot elements, and a step ofdetermining a parking maneuver to park the vehicle in the identifiedunoccupied parking slot. The method may also include a step ofcontrolling the vehicle to execute the set parking maneuver in anautomated or partially automated manner.

The identification of an unoccupied parking slot by using the parkingarea layout built based on a layout model allows to reduce the parkingmaneuver latency. In other words, the execution time of a parkingmaneuver executed by the vehicle in an automated or partially automatedmanner is significantly decreased. The detection of an unoccupiedparking slot can be performed earlier than in the prior art, since it isno longer necessary to pass by the unoccupied parking slot to start aparking maneuver. Furthermore, the parking maneuver can be significantlysimplified by planning a smoother and simpler trajectory for thevehicle.

The present method has another advantage that it does not requirespecific sensors and/or specific perception means.

In an embodiment, the one or more parameters associated with anidentified parking slot, extracted from the environmental information,includes at least one of the following elements: a position of theidentified parking slot relative to the vehicle; one or more dimensionsof the identified parking slot; an orientation of the identified parkingslot.

In an embodiment, updating over time the layout of the parking areaincludes generating over time first parking slot elements representingparking slots already identified from the environmental information, andpredicting second parking slot elements corresponding to parking slotsforeseen based on the parking slots already identified from theenvironmental information and the current layout model.

The parking area layout can extend beyond the parking slots that havealready been identified or detected, by addition of parking slotspredicted, or extrapolated, based on the layout model and the parkingslots already identified. This allows an earlier estimation of parkingslots location, which can reduce significantly the complexity of theparking maneuver by planning a simpler trajectory. It is not guaranteedthat a predicted or foreseen parking slot exists and is unoccupied. But,the parking slot will be confirmed or not confirmed later once moreenvironmental information has been obtained.

Advantageously, predicting the second parking slot elements includesplacing, or adding, parking slot elements outside of a sensing areacovered by the sensing system of the vehicle within the parking arealayout.

The present disclosure also concerns a computer program comprisinginstructions which, when the program is executed by a computer, causethe computer to carry out the method previously defined; a computingsystem comprising means adapted to execute the steps of the method; anda vehicle including the computing system.

BRIEF DESCRIPTION OF THE DRAWINGS

Other features, purposes and advantages of the disclosure will becomemore explicit by means of reading the detailed statement of thenon-restrictive embodiments made with reference to the accompanyingdrawings.

FIG. 1 schematically represents a vehicle including a computing systemof determining a parking area layout, according to an embodiment.

FIGS. 2A and 2B show a flowchart of a method of determining a layout fora parking area, according to an embodiment.

FIG. 3 illustrates an example of a parking area layout determined usingthe method of FIG. 2 .

DETAILED DESCRIPTION

Disclosed herein are methods of determining a layout for a parking area.The parking area may be a parking lot or a region of a parking lot. Sucha method can be used for example by a vehicle to determine a parkingarea layout and control the vehicle to move within the parking areabased on the parking area layout, in an automated or partially automatedmanner.

FIG. 1 shows a schematic functional block diagram of a vehicle 200.

The vehicle 200 includes a sensing system 300 in charge of sensing datain a surrounding environment of the vehicle 200. The sensing system 300may comprise multiple sensors, preferably of different types, such asradar sensor(s) 301, vision sensor(s) 302, ultrasonic sensor(s) 303,and/or lidar sensor(s) 304, etc. The vision sensors 302 may for exampleinclude one or more forward vision sensors 302 a and one or moresurround vision sensors 302 b.

Optionally, the sensing system 300 may further include a semantic layer,or function, or module, 305 responsible for determining semantic datafrom data provided by the sensors 301-304. The semantic data includessemantic information about the environment around the vehicle 200, inother words information in a syntactic form. It may relate for exampleto a traffic sign, a traffic regulation, a disabled parking slot, etc.The semantic layer 305 may be implemented by software and hardware.

The vehicle 200 may further include a perception stack or perceptionmodule 400. The perception stack 400 is responsible for determiningenvironmental information related to the surrounding environment of thevehicle 200 using sensing data provided by the sensing system 300. Itmay implement algorithms and/or applications and/or functions forprocessing sensing data from the sensing system 300 to determineenvironmental information about the surrounding environment of thevehicle 200. The perception stack 400 may have a plurality of perceptionlayers implementing respective algorithms and/or applications and/orfunctions for processing the sensing data to determine variousinformation about the surrounding environment of the vehicle 200. Forexample, the perception stack 400 may include: an occupancy grid mapgenerator 401 for generating an occupancy grid map of the surroundingenvironment of the vehicle 200 from the sensing data; and an objecttracker 402 for identifying and tracking dynamic objects in thesurrounding environment of the vehicle 200 from the sensing data.

The perception stack 400 may be implemented by software and hardware.The perception layers may use algorithms such as machine learningalgorithms.

In the present disclosure, the vehicle 200 further includes a system 500for tracking a parking area. The parking area can be a parking lot or aregion, or part, of the parking lot. The parking area tracking system500 has a function of determining a layout for a parking area.Optionally, the system 500 may have another function of determiningunoccupied or free parking slots, also termed as parking spaces, thatare locations designated for parking, in a parking area.

A layout of a parking area, or a parking area layout, is a schematicalrepresentation of the parking area, for example in geometric shapes. Itincludes parking slot elements representing respective parking slots ofthe parking area. Each parking slot element may have a predeterminedgeometric shape, for example a U shape or a rectangular shape. Theparking area layout may also include one or more aisle elementsrepresenting aisles, or traffic lanes, that are designated for movingwithin the parking lot or area.

The parking area tracking system 500 may include a parking area layouttracker 501 and a parking slot tracker 502.

The parking area layout tracker 501 is responsible for determining andupdating over time, or tracking, a layout for a parking area, asdescribed later in the method.

It should be noted that a parking area may use different arrangements ofparking slots in different parking areas or regions, respectively. Forexample, a parking area may use perpendicular parking in a main parkingarea and, in supplement, parallel parking in a limited parking area. Theparking area layout tracker 501 may determine a parking area layout foreach parking area, or region, using a specific arrangement of parkingslots.

The parking slot elements tracker 502 is responsible for determining andupdating over time, or tracking, the parking slot elements of theparking area layout, as described later in the method.

The parking area tracking system 500 may further include, or beconnected to, a database 550 of predefined parking lot layout models.Most of parking lots are designed, or arranged, in compliance with knownparking arrangements. There are at least three main types, orcategories, of parking: parallel, perpendicular and angle. In theparallel type, each parking slot is parallel to the direction in which avehicle is approaching the parking slot. In the perpendicular type, eachparking slot is perpendicular to the direction in which a vehicle isapproaching the parking slot. In the angle type, each parking slot formsan angle A with the direction in which a vehicle is approaching theparking slot represented by an arrow in FIG. 1 . The angle type may havemultiple variants depending on the angle. The most common angles used inthe angle type parking areas are 30°, 45° and 60° for the acute angle A.

FIG. 1 shows five different predefined parking lot layout models ofdifferent types including one parallel type, one perpendicular type, andthree angle types for the three respective acute angles A of 30°, 45°and 60°. The database 550 may further include, for each type of parking,multiple variants defined by different slot dimensions of the parkingslot. The slot dimensions include for example a slot width and a slotlength. Each parking lot layout model may be associated with a parkingslot template. In other words, each parking layout model may comprise anunderlaying parking slot template. Each parking slot template may becharacterized by a plurality of features including for example at leastone of: an angle of parking (e.g., 0°, 30°, 45°, 60° or 90°); a slotwidth; or a slot length.

The slot length may be a usable length of the parking slot, in otherwords the effective length that can be used by a vehicle to park.

Optionally, the parking area tracking system 500 may further include asemantic processing module 503 having the function of gathering semanticinformation about the surrounding environment of the vehicle 200 eitherfrom sensors 301-304, and/or from the semantic layer 305, and/or fromthe perception stack 400, and the function assigning special semanticinformation to parking slots and optionally to the layout. For example,if a special slot such as a parking slot for disabled person is sensed,the information “parking slot for disabled person” is assigned to theparking slot by the semantic processing module 503. The parking slottracker 502 may be configured to reject the parking slot, based on theinformation “parking slot for disabled person”, even if the slot isfree, or unoccupied, as the vehicle 200 is not authorized to park insuch a special slot.

The parking area tracking system 500 may be implemented by software andhardware.

The vehicle 200 may be an autonomous vehicle or at least partiallyautomated vehicle.

In an embodiment, the vehicle 200 may further comprise an automaticparking system 600 configured to at least partially control the vehicle200 to move in a parking area and/or perform a parking maneuver to parkinto a parking spot. The automatic parking system 600 may useinformation or data provided at the output of the parking area trackingsystem 500, as explained in the method described later. The automaticparking system 600 may be implemented by software and hardware.

The perception stack 400, the parking area tracking system 500 and/orthe automatic parking system 600 may be implemented on a same processoror controller, or on different processors or controllers.

A computer-implemented method of determining a parking layout for aparking area, according to an embodiment, will now be described withreference to FIGS. 2A, 2B, and 3 . A parking area may designate aparking lot or a region, or sub-area, of the parking lot.

Let's consider that the vehicle 200 enters a parking area 700, in a stepS0, and is moving in the parking area 700.

In a step S1 of detection of the environment, the sensing system 300 ofthe vehicle 200 collects information about a surrounding environment ofthe vehicle 200 with the sensors 301-304 in real time. In other words,the sensing system 300 monitors, senses in real time the surroundingenvironment or surrounding area of the vehicle with the sensors 301-304of the vehicle 200. The step S1 may be performed while the vehicle 200is moving in the parking area 700.

The sensing system 300 outputs sensing data, in a step S2. The sensingdata may include raw, or unprocessed, data and/or pre-processed dataprovided by the sensors 301-304. Optionally, the sensing data mayinclude semantic data about the surrounding environment of the vehicle200, provided by the semantic layer 305. Optionally, one or more sensors301-304 may have the capacity to determine semantic information fromsensing data. The sensing data contains information about theenvironment surrounding the vehicle 200.

At least part of the sensing data may be received as input by theperception stack or perception module 400. In a step S3, the sensingdata may be processed by the perception stack 400 to determineenvironmental information about the surrounding environment of thevehicle 200.

In an embodiment, in the step S3, the occupancy grid map generator 401may generate an occupancy grid map related to the environmentsurrounding the vehicle 200. The occupancy grid map represents a map ofan area surrounding the vehicle 200 as an evenly spaced field of binaryrandom variables each representing the presence of an obstacle at thatlocation in the area.

In the step S3, the object tracker 402 may identify and track dynamicobjects in the environment surrounding the vehicle 200.

The environmental information is continuously determined, updated, inreal time by the perception stack 400 from the sensing data continuouslyprovided by the sensing system 300 in real time.

In a reception step S4, the parking area tracking system 500 obtains, orreceives, the environmental information about the surroundingenvironment of the vehicle 200, provided by the perception stack 400.

Additionally, or alternatively, in the reception step S4, the parkingarea tracking system 500 may directly receive at least part of thesensing data from the sensing system 300, and process the receivedsensing data to determine environmental information about theenvironment surrounding the vehicle 200.

In an embodiment, in a step S5, the semantic processing layer 503 of theparking area tracking system 500 may gather semantic information fromthe sensors 301-304, and/or the semantic layer 305, and/or theperception stack 400, and provide it to the parking area layout tracker501 and to the parking slot tracker 502.

In a step S6, the parking area layout tracker 501 may identify, ordetect, parking slots in the environment around the vehicle 200 from theenvironmental information, obtained from the perception stack 400 and/orthe semantic processing layer 503 and/or the sensing system 300. Thetracker 501 may extract one or more parameters associated withidentified parking slots from the environmental information, by dataanalysis. For example, the parking area layout tracker 501 may identifyor detect road surface markings delineating the parking spots and/orparked vehicles and/or occupied parking slots and/unoccupied parkingslots, based on the obtained environmental information. The extractedparameters associated with the identified parking slots may include, foreach identified parking slot, at least part of the following features: aslot position relative to the vehicle 200, a slot width, a slot length,a parking orientation (e.g., parallel, perpendicular or angle) and/or aparking angle. Some extracted parameters might not be very accurate, andbe quantified by a range of values.

Then, in a step S7, the parking area layout tracker 501 determines oneor more parking layout models for the parking area based on theextracted one or more parameters. As previously indicated, in thedatabase 550, each layout model includes an underlaying parking slottemplate. The one or more extracted slot parameters associated with theone or more parking slots identified in the step S6 may be used asfilter or selection criteria to retrieve one or more parking layoutmodels from the database 550. A selection of one or more parking layoutmodels in the database 550 may thus be performed by only selecting theparking layout model(s) whose underlaying parking slot template matchesat least partially the extracted parameter(s). The parking layout modelsfrom the database 550, whose parking slot templates do not match anyparameter extracted from the environmental information, may be excludedfrom the selection.

Optionally, in a step S8, the parking area layout tracker 501 may obtainmap information related to a current location of the vehicle 200. Themap information may be used as an additional filter or selectioncriteria to select one or more parking layout models in the database550, in the step S7. The map information may be received from an onlinemapping platform to which the vehicle 200 is connected through a mobilecommunication network, and/or from a mapping application installed onthe vehicle 200.

Optionally, determining one or more parking layout models for theparking area may be further based on the semantic information about thesurrounding environment of the vehicle.

In a step S9, the parking area layout tracker 501 assigns a confidencescore to each of the parking layout models determined in the step S7.The confidence score assigned to each parking layout model indicates howthe corresponding underlaying parking slot template matches the one ormore extracted parameters of the parking slots identified from theenvironmental information. In other words, the confidence score assignedto each parking layout model quantifies a correspondence, a matching,between the parking slot template of this parking layout model and theone or more extracted slot parameter. The computation of the confidencescore can be executed by a computation algorithm for example based on analgorithm known as “intersection over union” that gives similarityvalues or coefficients from 0 to 1 and measures similarity between twosample sets or objects for object detection in images. The computationalgorithm may measure similarity between the parking slot template andthe identified parking slot in terms of orientation and/or dimensions.For each parking layout model, a similarity coefficient may be computedfor each identified or detected parking slot. Then, an overall score canbe calculated by combining the scores obtained for a plurality ofidentified parking slots, which gives the confidence score assigned tothis parking layout model.

The method further comprises a step S10, performed by the parking layouttracker 501, of selecting and updating over time a layout model for theparking area, based on the confidence scores assigned to the one or moreparking layout models. In the step S10, the parking layout tracker 501selects the layout model of the parking area having the highestconfidence score as a current layout model. The selected layout model isupdated over time, by the parking layout tracker 501, based on theconfidence scores assigned to the layout models generated from sensingdata collected while the vehicle is moving.

In the step S10, the current parking layout model is used by the parkinglayout tracker 501 to build, or determine, the parking area layout. Insome embodiments, all the features of the parking area layout may bederived from the current parking layout model. In other embodiment, somefeatures of the parking area layout may be derived from the extractedparameters of the identified parking slots. For example, the parkingarea layout may be based on a basic parking layout model, like one ofthe five models shown in FIG. 1 , but have a slot width and a slotlength determined from the extracted parameters.

The step S10 may be continuously executed in real time.

The steps S1 to S10 are performed in real time, continuously. While thevehicle 200 is moving in the parking area 700, its sensing system 300continuously collects information about the surrounding environment ofthe vehicle 200. In this way, the parking area tracking system 500 getsmore and more environmental information about the surroundingenvironment of the vehicle 200 over time. Over time, more and moreparking slots can be identified in the step S6, and the extracted slotparameters can become more and more precise. In the step S9, theconfidence scores assigned to the one or more parking layout models areupdated over time and are more and more reliable. This allows theparking area layout tracker 501 to converge over time to the correctparking layout model.

FIG. 3 represents an example of a parking area layout 800 including aplurality of parking slot elements 801, 802, . . . , representingparking slots of the parking area 700. In FIG. 3 , the parking arealayout 800 is superimposed on an occupancy grid map. In an embodiment,the parking slot elements may include: first parking slot elements,representing parking slots identified by the parking area layout tracker501 from the obtained environmental information; and second parking slotelements, corresponding to parking slots foreseen, or predicted, orextrapolated, by the parking area layout tracker 501, based on theparking slots already identified from the obtained environmentalinformation and the current parking layout model.

The prediction, or extrapolation, of the second parking slot elementsmay use environmental information and/or map information, for example aroad curve, and/or the presence of building(s) in the area, and/or thepresence of a wall at a certain distance to the vehicle 200, etc., toadjust the prediction or extrapolation.

Thus, the step S10 may include: generating the first parking slotelements representing the parking slots already identified from theobtained environmental information; and/or predicting the second parkingslot elements foreseen or extrapolated based on the parking slotsalready identified from the obtained environmental information and thecurrent parking layout model.

Predicting the second parking slot elements may include adding orplacing parking slot elements outside of a sensing area covered by thesensing system 300 of the vehicle 200, in the parking area layout 800.

The determined parking area layout may be used to control one or morefunctions of the vehicle 200. In some embodiments, the determinedparking area layout may be used to control a driving trajectory of thevehicle 200 and/or an Advanced Driver Assistance System, or ADAS,control function. For example, the parking area layout 800 may be usedby the automatic parking system 600, and/or by an automated drivingsystem, of the vehicle 200 to control the vehicle 200 to move within theparking area 700 in an automated manner or partially automated manner.Thus, the method may include a step of controlling one or more functionsof the vehicle 200 moving in the parking area 700 in an automated orpartially automated manner, by using the parking area layout 800. Thisallows to facilitate and secure the action of driving the vehicle 200 inthe parking area 700.

In an embodiment, the method may further include a step S11 of assigningan occupancy status score to each of the plurality of parking slotelements 801, 802, . . . of the parking area layout 800, and updatingthe occupancy status scores, based on the obtained environmentalinformation. The step S11 may be continuously performed by the parkingslot tracker 502, in real time. The occupancy status score of eachparking slot element 801, 802, . . . of the parking area layout 800indicates a probability of occupancy of the corresponding parking slotof the parking area 700.

In a particular embodiment, a score indicating an unoccupied status maybe assigned by default to each of the parking slot elements 801, 802, .. . of the parking area layout 800, unless the obtained environmentalinformation provides an occupancy indication, or evidence, for thecorresponding parking slot. The occupancy indication can be theindication that a vehicle is parked in the parking slot, or an object isdetected in the parking slot, or a part of a vehicle is detected in theparking slot.

The occupancy grid map produced by the generator 401 may also giveevidence about free, or unoccupied, space in a certain area. The parkingslot tracker 502 may rely on such information to determine if the areacan be considered as unoccupied, or unknown, or occupied, and assignoccupancy status scores to the parking slot elements.

The parking slot tracker 502 may also use the output of the semanticprocessing module 503 to assign special information to parking slotelements of the parking layout 800, for example the information that theparking slot is for a disabled person, in an optional step S12.

In a step S13, the parking slot tracker 502 may optionally perform asemantic classification of the parking slot elements 801, 802, . . . ofthe parking area layout 800, into different categories, based on thescores assigned to the parking slot elements and optionally specialinformation received from the semantic processing module 503. Thedifferent categories may include at least part of the followingcategories: unoccupied parking slot, occupied parking slot, unknownstatus, and/or special parking slot, for example parking slot fordisabled person.

The step S11, and the optional steps S12, S13 are continuously performedin real time, based on the environmental information continuouslyobtained. Thus, the occupancy status scores of the parking slot elements801, 802, . . . of the parking area layout 800 are continuously updatedin real time, based on the environmental information continuouslyobtained.

The automatic parking system 600 may have been initiated by a user, forexample when the vehicle 200 enters the parking area 700.

In an optional step S14, the automatic parking system 600 may controlthe vehicle 200 to move in the parking area to search for an unoccupiedparking slot suitable for parking, in an automated or at least partiallyautomated manner, based on the parking area layout 800.

The method may further include a step S15, performed by the parking slottracker 502, of identifying at least one unoccupied parking slotsuitable for parking in the parking area 700, based on the occupancystatus score assigned to each of the plurality of parking slot elementsof the parking area layout 800 and/or based on the result of theclassification of the parking slot elements performed in the step S13.This can be performed by comparing the occupancy status score of eachparking slot element with a predetermined threshold, and/or based on theparking slot categories resulting from the classification.

In a step S16, after identification or detection of at least oneunoccupied parking slot suitable for parking in the parking area 700 inthe step S13, the automatic parking system 600 may set or plan a parkingmaneuver to park the vehicle 200 in the unoccupied parking slot. If aplurality of unoccupied parking slots suitable for parking has beendetected, the automatic parking system 600 may select one of them, forexample the unoccupied parking slot closest to the vehicle 200.

Then, in a step S17, the automatic parking system 600 may control thevehicle 200 to execute the parking maneuver set or planned in the stepS16, to park the vehicle 200 in the unoccupied parking slot, in anautomated or partially automated manner. The parking maneuver may atleast include a movement of the vehicle 200 consisting in approachingthe unoccupied parking slot, used as a target parking slot. While thevehicle 200 is approaching this target parking slot, the parking arealayout and the occupancy status scores of the parking slot elements areupdated continuously, in real time. It may happen that the targetparking slot for the parking maneuver be finally identified as anoccupied parking slot. In that case, the automatic parking system 600repeats the steps S13 and S15 to park the vehicle 200 in another parkingslot.

The parking area layout may be displayed on a display apparatus of thevehicle 200. It may be superimposed on a map representing theenvironment of the vehicle 200. The parking area layout displayed on thedisplay apparatus may be used by a driver to facilitate the maneuvers inthe parking area 700.

The method may further include a step of generating a map based on theparking area layout. This map may be displayed on a display apparatus ofthe vehicle. The parking slot elements of the parking area layout may beclassified into three categories based on their occupancy status scores:unoccupied, occupied, unknown. The three categories may be representedby different colors on the display apparatus.

The present disclosure also concerns: a computer program comprisinginstructions which, when the program is executed by a computer, causethe computer to carry out the method previously defined; acomputer-readable data medium having stored thereon the computer programabove defined; a computing system having means adapted to execute thesteps of the method previously described; a vehicle including theabove-defined computing system; a computer-readable storage mediumincluding instructions that when executed configure a computing systemto execute the steps (operations) of the method previously described;and an apparatus including: a processor; and a computer-readable storagemedium having stored thereon instructions that, responsive to executionby the processor, cause the processor to execute the operations of themethod previously described. A computer-readable medium may benon-transitory.

The use of “example,” “advantageous,” and grammatically related termsmeans “serving as an example, instance, or illustration,” and not“preferred” or “advantageous over other examples.” Items represented inthe accompanying figures and terms discussed herein may be indicative ofone or more items or terms, and thus reference may be madeinterchangeably to single or plural forms of the items and terms in thiswritten description. The use herein of the word “or” may be considereduse of an “inclusive or,” or a term that permits inclusion orapplication of one or more items that are linked by the word “or” (e.g.,a phrase “A or B” may be interpreted as permitting just “A,” aspermitting just “B,” or as permitting both “A” and “B”), unless thecontext clearly dictates otherwise. Also, as used herein, a phrasereferring to “at least one of” a list of items refers to any combinationof those items, including single members. For instance, “at least one ofa, b, or c” can cover a, b, c, a-b, a-c, b-c, and a-b-c, as well as anycombination with multiples of the same element (e.g., a-a, a-a-a, a-a-b,a-a-c, a-b-b, a-c-c, b-b, b-b-b, b-b-c, c-c, c-c-c, or any otherordering of a, b, and c).

What is claimed is:
 1. A method comprising: determining environmentalinformation about a surrounding environment of a vehicle from sensingdata provided by a sensing system of the vehicle, while the vehicle ismoving in a parking area; determining a layout for the parking area by:extracting one or more parameters associated with parking slotsidentified from the environmental information; determining one or morelayout models for the parking area based at least one of the extractedone or more parameters, each layout model comprising an underlayingparking slot template; assigning to each of the determined layout modelsa confidence score, the confidence score indicating how the respectiveunderlaying parking slot template matches the one or more parametersassociated with the parking slots identified from the environmentalinformation; and selecting the layout model of the parking area havingthe highest confidence score as a current layout model used to determinethe parking area layout; and updating the selected layout model overtime based on the confidence scores assigned to the layout modelsgenerated from sensing data collected while the vehicle is moving. 2.The method according to claim 1, further comprising: using thedetermined parking area layout to control one or more functions of thevehicle.
 3. The method according to claim 1, wherein the determinedparking area layout is used to control at least one of a drivingtrajectory of the vehicle or an Advanced Driver Assistance System (ADAS)control function of the vehicle.
 4. The method according to claim 1,further comprising: assigning an occupancy status score to each of aplurality of parking slot elements of the layout of the parking area. 5.The method according to claim 4, further comprising: indicating aprobability of occupancy of the parking slot.
 6. The method according toclaim 5, further comprising: updating the occupancy status scores basedon the environmental information.
 7. The method according to claim 6,wherein a score indicating an unoccupied status is assigned by defaultto each of the parking slot elements of the layout of the parking area,unless the environmental information provides an occupancy indicationfor the parking slot element.
 8. The method according to claim 6,further comprising: identifying an unoccupied parking slot based on theoccupancy status score assigned to each of the plurality of parking slotelements.
 9. The method according to claim 8, further comprising:determining a parking maneuver to park the vehicle in the identifiedunoccupied parking slot.
 10. The method according to claim 1, whereinthe one or more parameters associated with an identified parking slot,extracted from the environmental information, includes at least one ofthe following elements: a position of the identified parking slotrelative to the vehicle; one or more dimensions of the identifiedparking slot; or an orientation of the identified parking slot.
 11. Themethod according to claim 1, wherein updating over time the layout ofthe parking area further comprises: generating over time first parkingslot elements representing parking slots already identified from theenvironmental information.
 12. The method according to claim 11, whereinupdating over time the layout of the parking area further comprises:predicting second parking slot elements corresponding to parking slotsforeseen based on the parking slots already identified from theenvironmental information and the current layout model.
 13. The methodaccording to claim 12, wherein predicting the second parking slotelements further comprises: placing parking slot elements outside of asensing area covered by the sensing system of the vehicle within theparking area layout.
 14. The method according claim 1, whereindetermining the one or more layout models further comprises: retrievingthe one or more layout models from a database storing a plurality ofpredefined layout models.
 15. The method according to claim 1, whereindetermining the environmental information about the surroundingenvironment of the vehicle from the sensing data provided by the sensingsystem of the vehicle further comprises at least one of: generating anoccupancy grid map of the environment of the vehicle; performing objecttracking in the environment of the vehicle; obtaining semanticinformation on the environment of the vehicle; or performing a semanticclassification of parking slots into different categories.
 16. Themethod according to claim 15, wherein determining the one or more layoutmodels for the parking area is further based on the semantic informationabout the surrounding environment of the vehicle.
 17. A non-transitorycomputer-readable storage medium comprising instructions that whenexecuted configure a computing system to: determine environmentalinformation about a surrounding environment of a vehicle from sensingdata provided by a sensing system of the vehicle, while the vehicle ismoving in a parking area; determine a layout for the parking area by:extract one or more parameters associated with parking slots identifiedfrom the environmental information; determine one or more layout modelsfor the parking area based at least one of the extracted one or moreparameters, each layout model comprising an underlaying parking slottemplate; assign to each of the determined layout models a confidencescore, the confidence score indicating how the respective underlayingparking slot template matches the one or more parameters associated withthe parking slots identified from the environmental information; andselect the layout model of the parking area having the highestconfidence score as a current layout model used to determine the parkingarea layout; and update the selected layout model over time based on theconfidence scores assigned to the layout models generated from sensingdata collected while the vehicle is moving.
 18. A computing systemconfigured to: determine environmental information about a surroundingenvironment of a vehicle from sensing data provided by a sensing systemof the vehicle, while the vehicle is moving in the parking area;determine a layout for the parking area by: extract one or moreparameters associated with parking slots identified from theenvironmental information; determine one or more layout models for theparking area based at least one of the extracted one or more parameters,each layout model comprising an underlaying parking slot template;assign to each of the determined layout models a confidence score, theconfidence score indicating how the respective underlaying parking slottemplate matches the one or more parameters associated with the parkingslots identified from the environmental information; and select thelayout model of the parking area having the highest confidence score asa current layout model used to determine the parking area layout; andupdate the selected layout model over time based on the confidencescores assigned to the layout models generated from sensing datacollected while the vehicle is moving.
 19. The computing systemaccording to claim 18, further comprising: a vehicle.